Lung cancer remains a significant public health issue and accounts for 28% of all cancer deaths in the United States. Most patients present with late stage disease, although up to 50% of those with clinical stage I non-small cell lung cancer (NSCLC) will develop metastasis within 5 years of the initial diagnosis. This suggests that many of the patients who undergo resection have undetectable metastasis at the time of presentation, and the only way to determine which patients will recur is with serial radiographs. The identification of specific biomarkers in the primary tumor that predicts metastasis would be an invaluable asset in the management of patients with NSCLC. In addition, identification of protein responsible for the development of metastatic disease has the potential to be a therapeutic target. This proposal is an extension of prior work in our laboratory, using a matrix assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) platform to elucidate protein biomarkers. We will generate protein expression profiles from early stage tumors that recur and compare this to tumors that do not recur. We will mine the data to determine differential expression of ion peaks, identify the proteins, and then validate the markers as biomarkers predictive of metastatic disease in a larger cohort series. This translational project will focus on an essential prognostic issue in lung cancer, but this model can be applied to any other diagnostic question in oncology.